
A cloud-based operation optimization of building energy systems using a hierarchical multi-agent control
Author(s) -
Alexander Kümpel,
Thomas Storek,
Marc Baranski,
Markus Schumacher,
Dirk Müller
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1343/1/012053
Subject(s) - cloud computing , distributed computing , scalability , computer science , interface (matter) , real time computing , control system , engineering , operating system , electrical engineering , bubble , maximum bubble pressure method
This work presents an agent-based control concept that we integrate into a cloud framework for controlling building energy systems. The agents are arranged in a hierarchical structure, where a coordinator agent sends optimized set point values to sub-agents. Each sub-agent controls a subsystem in order to reach the given set points and provides the coordinator agent with a cost function for the overall set point optimization. The multi-agent system and the building energy system exchange data via the cloud framework FIWARE. The components of the building energy system (e.g. boiler, air-handling unit) are connected to the cloud framework and send measurements (e.g. temperature values or volume flow) via a scalable IoT-Interface to the corresponding data object in the platform. The sub-agents of the agent control receive the measurements and send the calculated control action back to the corresponding components of the energy system. In a simulation study, we use the framework to control an air-handling unit. The aim of the agent control is to reach a given supply air temperature while reducing the total consumed energy. The implemented cloud-based control is capable of efficiently reaching the given temperature set points while communicating via the IoT interface.